Results 121 to 130 of about 405,044 (354)

Artificial intelligence (AI) learning tools in K-12 education: A scoping review

Journal of Computers in Education
Artificial intelligence (AI) literacy is a global strategic objective in education. However, little is known about how AI should be taught. In this paper, 46 studies in academic conferences and journals are reviewed to investigate pedagogical strategies,
I. H. Y. Yim, Jiahong Su
semanticscholar   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Functions and Frames in the Learning of Structures [PDF]

, 1973
Work reported herein was conducted at the Artificial Intelligence Laboratory, a Massachusetts Institute of Technology research program supported in part by the Advanced Research Projects Agency of the Department of Defense and monitored by the Office of ...
Freiling, Michael J.
core  

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

Advanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Selma Amara, Georgian Melinte, Xixiang Zhang, Gianluca Setti   +8 more
wiley   +1 more source

3D Printing Innovations in Polymeric Porous and Patterned Architecture

Advanced Functional Materials, EarlyView.
Polymeric foams occupy a unique structural space between dense solids and open networks, where engineered void fraction governs mechanical compliance, thermal resistance, and mass transport. Additive manufacturing now enables precise spatial control over cellular architecture, unlocking designer foam structures across applications spanning crash ...
Dhanush Patil, Sri Vaishnavi Thummalapalli, Clarissa Westover, Arunachalam Ramanathan, M. Taylor Sobzcak, Roumika Patil, Qixuan Xiang, Tiantian Li, Sui Yang, Timothy E. Long, Hongyue Sun, Xianqiao Wang, Yang Liu, Kenan Song   +13 more
wiley   +1 more source

Machine Learning and Artificial Intelligence in Nanomedicine

WIREs Nanomedicine and Nanobiotechnology
ABSTRACTNanomedicine harnesses nanoscale materials, such as lipid, polymeric, and inorganic nanoparticles, to deliver diagnostic or therapeutic agents for cancer, infectious disease, and neurological disorders, among others. However, translating promising nanoparticle designs into clinically approved products remains a challenge.
Wei‐Chun Chou, Alexa Canchola, Fan Zhang, Zhoumeng Lin   +3 more
openaire   +4 more sources

Multimodal Perception and Machine Learning‐Empowered Human Machine Interfaces With Double‐Network Hydrogel Fibers

Advanced Functional Materials, EarlyView.
This work develops polyacrylamide‐alginate (PAM‐Alg) double‐network hydrogel fibers for multimodal perception and intelligent human‐machine interfaces. The covalent‐ionic network provides high strength, toughness, and stable conductivity. Easily woven into wearables and integrated with soft robots, the fibers enable object and temperature recognitions ...
Yujue Yang, Minyu Qiu, Di Tan, Xinlong Liu, Junze Zhang, Ziyu He, Jing Han, Yuanyuan Gao, Zihua Li, Hong Fu, Bingang Xu   +10 more
wiley   +1 more source

Optimal subset selection for active learning

, 2011
Active learning traditionally relies on instance based utility measures to rank and select instances for labeling, which may result in labeling redundancy. To address this issue, we explore instance utility from two dimensions: individual uncertainty and
Fu, Yifan, Fu, Y, Zhu, X, Zhu, Xingquan
core   +1 more source

Solution‐Processed Thin‐Film Transistors With Tunable Temporal Dynamics for Neuromorphic Computing

Advanced Functional Materials, EarlyView.
Solution‐processed CNT and CNT/P3HT ion‐gated transistors exhibit materials‐defined synaptic timescales: fast CNT devices for high‐frequency spiking and slow hybrid devices for temporal integration. Embedding these dynamics into coupled reservoir‐computing and spiking neural network simulations reveals that a Hybrid‐Reservoir / CNT‐SNN architecture ...
Kevin Schnittker, Haoyi Lin, Zahra Bahrami, Strahinja Marinkovic, Sung Hyun Lee, Joseph Andrews   +5 more
wiley   +1 more source

Learning a hybrid architecture for sequence regression and annotation

, 2016
© Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.When learning a hidden Markov model (HMM), sequential observations can often be complemented by real-valued summary response variables ...
Zhang, Yizhe, Carin, L, Carin, Lawrence, Hartemink, AJ, Zhong, J, Henao, R, Henao, Ricardo, Zhang, Y, Hartemink, Alexander, Zhong, Jianling   +9 more
core   +1 more source